The demand for custom content and instant response in digital marketing is booming. Not only is the volume of content skyrocketing, but also the expectation of audience-specific optimization. To tap into this growing opportunity, marketers must go beyond improving their production efficiency; they must also expose their creative processes to data analytics.
The role of data in driving marketing decisions is only increasing. That means creatives and analysts will be forced to embrace a new level of collaboration. While the two have long-since been allies, they are not usually close partners-in-crime. A two-way street of creative ideation and critical analysis must be paved, even if it’s a road oft-not taken. This project is not optional; it will be table stakes just to stay in the game.
Amplifying this challenge, the volume of data available to marketers is growing at a 2x annual clip. The scalability of analytics, therefore, will be just as vital as its accuracy and value. The solution to this challenge is straightforward: the automation of analytics wherever possible, enabled by new technologies.
Empowered with new tools, the increased scale of analysis will bring with it a democratization of analytics within organizations. You will no longer have to be a data scientist to glean meaning from data. Whereas the structuring and cleaning of data can be a high-skill, time-intensive activity, the act of interpreting data and generating insights can be—and should be—a more universal, shared experience. So, organizations must reflect that, by doing away with analysis siloing and facilitating collaboration across roles and teams.
Analytics for the masses
It’s clear that in the post-digital era, every role in marketing—from media buyer to account leader to CMO—must embrace a new vision of analytics. Marketers must begin to see analytics more as a process, a way of thinking and approaching problems, rather than just an organization’s department. Role-based, manual analytics makes it difficult for marketers to reliably access valuable insights. Once analytics becomes more of a shared, distributed process than an FTE cost-center, it not only empowers the surrounding organization: it also places upon it a new responsibility.
In short, due to automation, analytics must become a more decentralized, grassroots effort, rather than a top-down, centralized function. Rather than throwing more analyst bodies at a problem, organizations need processes and tools for allowing more people to use analytics to tackle that problem.
From data insights to data storytelling
As traditional analytics workflows become increasingly automated, analyst roles within the organization will change drastically. Analysts will have more time to focus on creative problem-solving. What is currently an analytics 'labor force' in most organizations is going to morph into an analytics “brain force” as analysts transition from “data janitors” to “data storytellers.”
Today, most analysts organize their week around repetitive reporting deadlines. Those deadlines translate into clearly-defined reporting templates, which are just reliable ensembles of textual or visual data insights: Creative performance by audience; Media performance week-over-week; Weekly average versus benchmarks; Spend breakdown by platform; and so on. Marketers rely on the regular delivery of these insights to drive their decisions; but what is reliable for a marketer becomes redundant, even robotic, for the analyst. Insight generation is ripe for automation because it is so repetitive.
The true value of analytics lies not in the science of generating insights, but rather in the art of fitting those insights together into larger narratives. By piecing together insights like frames in a film, analysts can provide marketers with more powerful stories to inform their creative strategies. In the past, analysts didn’t have much time for interpretive storytelling. But, thanks to automation, that is changing.
Et tu, Marketer
This transformation will potentially impact marketers even more than analysts. The current teleological model—where marketers create stories, then look to analytics to retroactively provide supporting data—is going to be flipped. Creatives will be expected to develop assets that reflect a data-backed strategy. Simultaneously, analysts will have to become more innovative in their synthesis of data inputs.
As analytics morphs from role to process and permeates the entire organization, it will become more fully integrated into the DNA of marketing itself. Organizations should use technology to automate repetitive processes while empowering marketers and analysts to collaborate to fuse insights creatively. In other words, businesses should acknowledge what computers are better at while focusing human capital on the things people do best.
As marketers’ reliance on analytics increases, the deeper insights they’ll get from analytics will free them up to be even more creative. Marketers will gain greater, more nuanced insights into consumer differences at speeds enabling near-instantaneous response. And they’ll be equipped to serve the kind of ultra-customized creative that’s going to be the key to marketing success in the post-digital era and a post-analytics marketing world.
Alex Nunnelly, senior director of analytics, Panoramic